A data-driven method for syndrome type identification and classification in traditional Chinese medicine

Nevin Lianwen ZHANG, Chen FU, Teng-Fei LIU, Bao-Xin CHEN, Kin Man POON, Pei Xian CHEN, Yun-ling ZHANG

Research output: Contribution to journalArticle

6 Citations (Scopus)


The efficacy of traditional Chinese medicine (TCM) treatments for Western medicine (WM) diseases relies heavily on the proper classification of patients into TCM syndrome types. The authors developed a data-driven method for solving the classification problem, where syndrome types were identified and quantified based on statistical patterns detected in unlabeled symptom survey data. The new method is a generalization of latent class analysis (LCA), which has been widely applied in WM research to solve a similar problem, i.e., to identify subtypes of a patient population in the absence of a gold standard. A well-known weakness of LCA is that it makes an unrealistically strong independence assumption. The authors relaxed the assumption by first detecting symptom co-occurrence patterns from survey data and used those statistical patterns instead of the symptoms as features for LCA. This new method consists of six steps: data collection, symptom co-occurrence pattern discovery, statistical pattern interpretation, syndrome identification, syndrome type identification and syndrome type classification. A software package called Lantern has been developed to support the application of the method. The method was illustrated using a data set on vascular mild cognitive impairment. Copyright © 2017 Journal of Integrative Medicine Editorial Office.
Original languageEnglish
Pages (from-to)110-123
JournalJournal of integrative medicine
Issue number2
Publication statusPublished - Mar 2017


Chinese Traditional Medicine
Blood Vessels
Surveys and Questionnaires


Zhang, N. L., Fu, C., Liu, T. F., Chen, B.-X., Poon, K. M., Chen, P. X., et al. (2017). A data-driven method for syndrome type identification and classification in traditional Chinese medicine. Journal of Integrative Medicine, 15(2), 110-123.


  • Medicine, Chinese traditional
  • Syndrome
  • Syndrome classification
  • Latent tree analysis
  • Symptom co-occurrence patterns
  • Patient clustering
  • Stand syndrome differentiation